Waste recycling: share in the structure of the tariff for the treatment of solid municipal waste in the Vologda region
Bibliographic record
Abstract
In the modern world, the issues of solid municipal waste disposal, as part of the problem of environmental protection, are quite acute These problems are relevant for Russia and for many other world powers. The Russian Federation is one of the most polluted countries in the world, which negatively affects the quality of life and the health of the population of its regions. The annual increase in the volume of municipal solid waste is part of the man-made impact of man on the natural environment. To make strategic decisions on this issue, it is necessary to understand the policy of MSW management, so the authors in the article consider the values of tariffs for MSW management in one of the major regions of Russia - the Vologda Region. The data of tariffs of the Vologda region approved for 2021 are given. The structure of the average tariffs of the Russian Federation and the Vologda Region is analyzed. On the basis of regional regulations, a sample of data on the costs of disposal and transportation of MSW for some districts of the Vologda region is given: Velikoustugski, Totemski, Mezhdurechensky, Babushkinsky area, Belozersky districts. The average values of tariffs for the treatment of MSW for Russia and other countries are given: the USA, Canada, Germany, France and Finland. In addition to tariffs, the authors conducted a study on the distribution of MSW by type of disposal: disposal, incineration and recycling The article discusses the values of tariffs for the treatment of solid municipal waste and their disposal. In conclusion, the authors express concern about insufficient funds for innovations in the field of MSW processing/ recycling.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".